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What is Branch and Bound Method

Research Advancements in Smart Technology, Optimization, and Renewable Energy
This is a solution method which partitions the feasible solution space into smaller subsets of solutions.
Published in Chapter:
The Traveling Salesman Problem: Network Properties, Convex Quadratic Formulation, and Solution
Elias Munapo (North-West University, South Africa)
DOI: 10.4018/978-1-7998-3970-5.ch006
Abstract
The chapter presents a traveling salesman problem, its network properties, convex quadratic formulation, and the solution. In this chapter, it is shown that adding or subtracting a constant to all arcs with special features in a traveling salesman problem (TSP) network model does not change an optimal solution of the TSP. It is also shown that adding or subtracting a constant to all arcs emanating from the same node in a TSP network does not change the TSP optimal solution. In addition, a minimal spanning tree is used to detect sub-tours, and then sub-tour elimination constraints are generated. A convex quadratic program is constructed from the formulated linear integer model of the TSP network. Interior point algorithms are then applied to solve the TSP in polynomial time.
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More Results
Improving the Optimality Verification and the Parallel Processing of the General Knapsack Linear Integer Problem
This is a solution method which partitions the feasible solution space into smaller subsets of solutions.
Full Text Chapter Download: US $37.50 Add to Cart
New Direction to the Scheduling Problem: A Pre-Processing Integer Formulation Approach
This is a solution method which partitions the feasible solution space into smaller subsets of solutions.
Full Text Chapter Download: US $37.50 Add to Cart
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